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Abstract:

Embodiments of the invention allow an institution to obtain a more
comprehensive view of its exposure to one or more entities or groups of
entities and, in some cases, to use this information to identify
opportunities for and/or risks to the institution. For example,
embodiments of the invention involve systems and methods for: (1)
selecting an entity; (2) determining exposure to the entity in isolation;
(3) determining one or more related entities based on transaction data
associated with the selected entity; (4) determining exposure to the one
or more related entities; and (5) combining the exposure data for the
selected entity and the related entities to obtain comprehensive exposure
metrics for the selected entity. Some embodiments of the invention
further involve aggregating the comprehensive entity exposure metrics for
several entities based on entity characteristics to create other exposure
metrics, and then displaying exposure metrics to a user on a display
based on user-selected entities or entity characteristics.

Claims:

1. An apparatus comprising: a memory comprising account information
stored therein about a plurality of accounts, the account information
comprising transaction information and exposure information for each of
the plurality of accounts; and a processor communicably coupled to the
memory, the processor configured to: identify a selected entity, use the
transaction information to identify one or more related entities that are
related to the selected entity, use the account information to identify
exposure information for the one or more related entities, and determine
a comprehensive view of the exposure to the selected entity based at
least in part on the exposure information of the one or more related
entities.

2. The apparatus of claim 1, wherein the processor is configured to: use
the account information to identify information about direct exposure to
the selected entity in isolation; and determine the comprehensive view of
the exposure to the selected entity based at least in part on a
combination of the exposure information of the one or more related
entities and the information about direct exposure to the selected
entity.

3. The apparatus of claim 2, wherein the processor is configured to
determine the comprehensive view of the exposure to the selected entity
by adding together the exposure information of the one or more related
entities and the information about direct exposure to the selected
entity.

4. The apparatus of claim 2, wherein the processor is configured to:
apply weighting factors to the exposure information of the one or more
related entities; and determine the comprehensive view of the exposure to
the selected entity based at least in part on the weighting factors, the
exposure information of the one or more related entities, and the
information about direct exposure to the selected entity.

5. The apparatus of claim 4, wherein the processor is configured to: use
the transaction information to identify a type of relationship between
the one or more related entities and the selected entity; and apply the
weighting factors to the exposure information of the one or more related
entities based at least in part on the type of relationship.

6. The apparatus of claim 1, further comprising: a communication
interface communicably coupled to the processor and a display device,
wherein the processor is further configured to use the communication
interface to present on the display device the comprehensive view of the
exposure to the selected entity.

7. The apparatus of claim 1, wherein the processor is further configured
to: determine comprehensive exposure information for each of a plurality
of selected entities; and aggregate the comprehensive views for a subset
of the plurality of selected entities based on a common characteristic
shared by the subset of the plurality of selected entities.

8. The apparatus of claim 7, further comprising: a user interface
configured to receive a user-selected characteristic from a user, wherein
the processor is configured to, in response to receiving the
user-selected characteristic from the user, present the user with
information about an aggregate of the comprehensive views for a subset of
the plurality of selected entities, where the subset of the plurality of
selected entities share the user-selected characteristic.

9. The apparatus of claim 7, wherein the common characteristic comprises
a sector of the economy, an industry, or a geographic indicator.

10. The apparatus of claim 1, wherein the account information comprises
information about accounts that customers have with an institution,
wherein the transaction information comprises information about
transactions processed at least in part by the institution for the
customers, wherein the exposure information for the one or more related
entities comprises the institution's exposure to the one or more related
entities, and wherein the comprehensive view of the exposure to the
selected entity comprises an estimate of the institution's exposure to
the selected entity based at least in part on the one or more related
entities.

12. The apparatus of claim 1, wherein the selected entity comprises a
company, and wherein the one or more related entities comprise employees
of the company.

13. The apparatus of claim 1, wherein the selected entity comprises a
company, and wherein the one or more related entities comprise suppliers,
distributors, contractors, or affiliates of the company.

14. The apparatus of claim 1, wherein the selected entity comprises an
individual, and wherein the one or more related entities comprise an
employer of the individual.

15. The apparatus of claim 1, wherein the transaction information
comprises information about direct deposit, Automated Clearing House
(ACH), check, payment, or payroll transactions, and wherein the processor
is configured to identify the one or more related entities as being
related to the selected entity based on the selected party engaging in a
pre-defined frequency of direct deposit, Automated Clearing House (ACH),
check, payment, or payroll transactions with the one or more related
entities.

16. The apparatus of claim 1, wherein the processor is configured to
identify the one or more related entities as being related to the
selected entity based on the selected party engaging in a pre-defined
frequency of transactions with the one or more related entities.

17. The apparatus of claim 1, wherein the exposure information for the
one or more related entities comprises an institution's credit exposure
to the one or more related entities, and wherein the comprehensive view
of the exposure to the selected entity comprises an estimate of the
institution's credit exposure to the selected entity based at least in
part on the one or more related entities.

18. The apparatus of claim 17, wherein the credit exposure comprises loan
or line of credit balances.

19. The apparatus of claim 1, wherein the exposure information for the
one or more related entities comprises an institution's revenue exposure
to the one or more related entities, and wherein the comprehensive view
of the exposure to the selected entity comprises an estimate of the
institution's revenue exposure to the selected entity based at least in
part on the one or more related entities.

20. The apparatus of claim 1, wherein the memory comprises
computer-executable program code stored therein, and wherein the
processor is configured to perform the functions recited in claim 1 by
executing the computer-executable program code.

21. A method comprising: accessing a memory comprising account
information stored therein about a plurality of accounts, the account
information comprising transaction information and exposure information
for each of the plurality of accounts; identifying a selected entity;
using a computer to automatically identify, from the transaction
information, one or more related entities that are related to the
selected entity; using a computer to automatically gather, from the
account information, exposure information for the one or more related
entities; and using a computer to determine a comprehensive view of the
exposure to the selected entity based at least in part on the exposure
information of the one or more related entities.

22. The method of claim 21, further comprising: using the account
information to identify information about direct exposure to the selected
entity in isolation; and using a computer to determine the comprehensive
view of the exposure to the selected entity based at least in part on a
combination of the exposure information of the one or more related
entities and the information about direct exposure to the selected
entity.

23. The method of claim 21, further comprising: using the transaction
information to identify a type of relationship between the one or more
related entities and the selected entity; applying weighting factors to
the exposure information of the one or more related entities based at
least in part on the type of relationship; and determining the
comprehensive view of the exposure to the selected entity based at least
in part on the weighting factors, the exposure information of the one or
more related entities, and the information about direct exposure to the
selected entity.

24. The method of claim 21, further comprising: determining comprehensive
exposure information for each of a plurality of selected entities; and
aggregating the comprehensive views for a subset of the plurality of
selected entities based on a common characteristic shared by the subset
of the plurality of selected entities.

25. The method of claim 21, wherein the account information comprises
information about accounts that customers have with an institution,
wherein the transaction information comprises information about
transactions processed at least in part by the institution for the
customers, wherein the exposure information for the one or more related
entities comprises the institution's exposure to the one or more related
entities, and wherein the comprehensive view of the exposure to the
selected entity comprises an estimate of the institution's exposure to
the selected entity based at least in part on the one or more related
entities.

27. The method of claim 21, wherein the selected entity comprises a
company, and wherein the one or more related entities comprise employees
of the company.

28. The method of claim 21, wherein the transaction information comprises
information about direct deposit, Automated Clearing House (ACH), check,
payment, or payroll transactions, and wherein the method further
comprises: identifying the one or more related entities as being related
to the selected entity based on the selected party engaging in a
pre-defined frequency of direct deposit, Automated Clearing House (ACH),
check, payment, or payroll transactions with the one or more related
entities.

29. The method of claim 21, further comprising: identifying the one or
more related entities as being related to the selected entity based on
the selected party engaging in a pre-defined frequency of transactions
with the one or more related entities.

30. The method of claim 1, wherein the exposure information for the one
or more related entities comprises an institution's credit exposure to
the one or more related entities, and wherein the comprehensive view of
the exposure to the selected entity comprises an estimate of the
institution's credit exposure to the selected entity based at least in
part on the one or more related entities.

31. The method of claim 30, wherein the credit exposure comprises loan or
line of credit balances.

32. The method of claim 1, wherein the exposure information for the one
or more related entities comprises an institution's revenue exposure to
the one or more related entities, and wherein the comprehensive view of
the exposure to the selected entity comprises an estimate of the
institution's revenue exposure to the selected entity based at least in
part on the one or more related entities.

33. A computer program product comprising a non-transitory computer
readable medium having computer-executable program code stored therein,
wherein the computer-executable program code comprises: a first code
portion configured to access a memory comprising account information
stored therein about a plurality of accounts, the account information
comprising transaction information and exposure information for each of
the plurality of accounts; a second code portion configured to identify a
selected entity; a third code portion configured to identify, from the
transaction information, one or more related entities that are related to
the selected entity; a fourth code portion configured to gather, from the
account information, exposure information for the one or more related
entities; and a fifth code portion configured to determine a
comprehensive view of the exposure to the selected entity based at least
in part on the exposure information of the one or more related entities.

34. The computer program product of claim 33, further comprising: a sixth
code portion configured to use the account information to identify
information about direct exposure to the selected entity in isolation,
wherein the fifth code portion is configured to determine the
comprehensive view of the exposure to the selected entity based at least
in part on a combination of the exposure information of the one or more
related entities and the information about direct exposure to the
selected entity.

35. The computer program product of claim 33, further comprising: a sixth
code portion configured to use the transaction information to identify a
type of relationship between the one or more related entities and the
selected entity; and a seventh code portion configured to apply weighting
factors to the exposure information of the one or more related entities
based at least in part on the type of relationship, wherein the fifth
code portion is configured to determine the comprehensive view of the
exposure to the selected entity based at least in part on the weighting
factors, the exposure information of the one or more related entities,
and the information about direct exposure to the selected entity.

36. The computer program product of claim 33, further comprising: a sixth
code portion configured to identify the one or more related entities as
being related to the selected entity based on the selected party engaging
in a pre-defined frequency of transactions with the one or more related
entities.

37. The computer program product of claim 33, wherein the exposure
information for the one or more related entities comprises an
institution's credit exposure to the one or more related entities, and
wherein the comprehensive view of the exposure to the selected entity
comprises an estimate of the institution's credit exposure to the
selected entity based at least in part on the one or more related
entities.

Description:

FIELD

[0001] Embodiments of the invention relate to apparatuses and methods for
determining the exposure of an organization to one or more entities or
groups of entities.

BACKGROUND

[0002] Businesses are always looking for new opportunities and evaluating
the risk associated with both existing opportunities and possible new
opportunities. As such, businesses are often interested to know where
they are overexposed and underexposed to particular current customers,
groups of current customers, potential customers, and groups of potential
customers. For example, many financial institutions lend money to
customers in the form of loans and lines of credit. It is important for
these financial institutions to have an accurate view of their exposure
to risk associated with these loans and lines of credit. With an accurate
picture of the financial institution's exposure to risk, new
opportunities may become apparent in areas where the financial
institution is underexposed to risk. In areas where the financial
institution determines that it is overexposed to risk, the financial
institution can take appropriate actions to reduce or hedge the risk in
those areas.

[0003] Unfortunately, however, it can be difficult for many businesses,
especially large businesses, to accurately determine and easily assess
the business's current or potential exposure to a customer or group of
customers due to the complexity of the economy and interrelationships
between customers. Current techniques and systems used to determine a
business's exposure to customers or groups of customers are generally
primitive and fail to give a full and accurate picture of the
complexities of a business's exposure profile.

BRIEF SUMMARY

[0004] Embodiments of the present invention address the above needs and/or
achieve other advantages by providing apparatuses (e.g., systems,
computer program products, machines, and/or other devices) and methods
that provide for a more comprehensive exposure analysis and that further
provide mechanisms for more easily viewing the results of the
comprehensive exposure analysis. More specifically, embodiments of the
invention allow an institution to obtain a more comprehensive view of its
exposure to one or more entities or groups of entities and, in some
cases, to use this information to identify opportunities for and/or risks
to the institution. For example, embodiments of the invention involve
systems and methods for: (1) selecting an entity; (2) determining
exposure to the entity in isolation; (3) determining one or more related
entities based on transaction data associated with the selected entity;
(4) determining exposure to the one or more related entities; and (5)
combining the exposure data for the selected entity and the related
entities to obtain comprehensive exposure metrics for the selected
entity. Some embodiments of the invention further involve aggregating the
comprehensive entity exposure metrics for several entities based on
entity characteristics to create other exposure metrics, and then
displaying exposure metrics to a user on a display based on user-selected
entities or entity characteristics.

[0005] For example, embodiments of the invention provide an apparatus
including a memory having account information stored therein about a
plurality of accounts. The account information includes transaction
information and exposure information for each of the plurality of
accounts. The apparatus also includes a processor communicably coupled to
the memory and configured to: (1) identify a selected entity; (2) use the
transaction information to identify one or more related entities that are
related to the selected entity, (3) use the account information to
identify exposure information for the one or more related entities, and
(4) determine a comprehensive view of the exposure to the selected entity
based at least in part on the exposure information of the one or more
related entities. Some embodiments of the apparatus further include a
communication interface communicably coupled to the processor and a
display device, wherein the processor is further configured to use the
communication interface to present on the display device the
comprehensive view of the exposure to the selected entity.

[0006] In some embodiments of the apparatus, the processor is configured
to use the account information to identify information about direct
exposure to the selected entity in isolation, and further configured to
determine the comprehensive view of the exposure to the selected entity
based at least in part on a combination of the exposure information of
the one or more related entities and the information about direct
exposure to the selected entity. In some such embodiments, the processor
is configured to determine the comprehensive view of the exposure to the
selected entity by adding together the exposure information of the one or
more related entities and the information about direct exposure to the
selected entity. In some such embodiments, the processor is configured to
apply weighting factors to the exposure information of the one or more
related entities, and further configured to determine the comprehensive
view of the exposure to the selected entity based at least in part on the
weighting factors, the exposure information of the one or more related
entities, and the information about direct exposure to the selected
entity. For example, the processor may be configured to use the
transaction information to identify a type of relationship between the
one or more related entities and the selected entity, and further
configured to apply the weighting factors to the exposure information of
the one or more related entities based at least in part on the type of
relationship.

[0007] In some embodiments of the apparatus, the processor is further
configured to: determine comprehensive exposure information for each of a
plurality of selected entities; and aggregate the comprehensive views for
a subset of the plurality of selected entities based on a common
characteristic shared by the subset of the plurality of selected
entities. In some such embodiments, the apparatus includes a user
interface configured to receive a user-selected characteristic from a
user, and the processor is configured to, in response to receiving the
user-selected characteristic from the user, present the user with
information about an aggregate of the comprehensive views for a subset of
the plurality of selected entities, where the subset of the plurality of
selected entities share the user-selected characteristic. The common
characteristic may include, for example, a sector of the economy, an
industry, or a geographic indicator.

[0008] In some embodiments of the apparatus, the account information
includes information about accounts that customers have with an
institution, the transaction information includes information about
transactions processed at least in part by the institution for the
customers, the exposure information for the one or more related entities
includes the institution's exposure to the one or more related entities,
and the comprehensive view of the exposure to the selected entity
includes an estimate of the institution's exposure to the selected entity
based at least in part on the one or more related entities. For example,
the institution may be a bank, the accounts may be bank accounts, and the
transactions may be financial transactions.

[0009] In some embodiments of the apparatus, the selected entity is a
company and the one or more related entities are employees of the
company. In some embodiments, selected entity is a company and the one or
more related entities are suppliers, distributors, contractors, or
affiliates of the company. In other embodiments, the selected entity is
an individual and the one or more related entities include an employer of
the individual.

[0010] In some embodiments of the apparatus, the transaction information
includes information about direct deposit, Automated Clearing House
(ACH), check, payment, or payroll transactions, and the processor is
configured to identify the one or more related entities as being related
to the selected entity based on the selected party engaging in a
pre-defined frequency of direct deposit, ACH, check, payment, or payroll
transactions with the one or more related entities.

[0011] In some embodiments of the apparatus, the processor is configured
to identify the one or more related entities as being related to the
selected entity based on the selected party engaging in a pre-defined
frequency of transactions with the one or more related entities.

[0012] In some embodiments, the exposure information for the one or more
related entities includes an institution's credit exposure to the one or
more related entities, and the comprehensive view of the exposure to the
selected entity includes an estimate of the institution's credit exposure
to the selected entity based at least in part on the one or more related
entities. In some such embodiments, the credit exposure includes loan or
line of credit balances. In other embodiments of the apparatus, the
exposure information for the one or more related entities includes an
institution's revenue exposure to the one or more related entities, and
the comprehensive view of the exposure to the selected entity includes an
estimate of the institution's revenue exposure to the selected entity
based at least in part on the one or more related entities.

[0013] Embodiments of the invention also provide a method involving: (1)
accessing a memory comprising account information stored therein about a
plurality of accounts, the account information comprising transaction
information and exposure information for each of the plurality of
accounts; (2) identifying a selected entity; (3) using a computer to
automatically identify, from the transaction information, one or more
related entities that are related to the selected entity; (4) using a
computer to automatically gather, from the account information, exposure
information for the one or more related entities; and (5) using a
computer to determine a comprehensive view of the exposure to the
selected entity based at least in part on the exposure information of the
one or more related entities. The method may further involve: using the
account information to identify information about direct exposure to the
selected entity in isolation; and using a computer to determine the
comprehensive view of the exposure to the selected entity based at least
in part on a combination of the exposure information of the one or more
related entities and the information about direct exposure to the
selected entity.

[0014] In some embodiments, the method further includes: using the
transaction information to identify a type of relationship between the
one or more related entities and the selected entity; applying weighting
factors to the exposure information of the one or more related entities
based at least in part on the type of relationship; and determining the
comprehensive view of the exposure to the selected entity based at least
in part on the weighting factors, the exposure information of the one or
more related entities, and the information about direct exposure to the
selected entity. In some embodiments, the method includes: determining
comprehensive exposure information for each of a plurality of selected
entities; and aggregating the comprehensive views for a subset of the
plurality of selected entities based on a common characteristic shared by
the subset of the plurality of selected entities.

[0015] In some embodiments of the method, the transaction information
includes information about direct deposit, Automated Clearing House
(ACH), check, payment, or payroll transactions, and the method further
involves: identifying the one or more related entities as being related
to the selected entity based on the selected party engaging in a
pre-defined frequency of direct deposit, Automated Clearing House (ACH),
check, payment, or payroll transactions with the one or more related
entities.

[0016] In some embodiments, the method involves identifying the one or
more related entities as being related to the selected entity based on
the selected party engaging in a pre-defined frequency of transactions
with the one or more related entities.

[0017] Embodiments of the invention also provide a computer program
product comprising a non-transitory computer readable medium having
computer-executable program code stored therein, wherein the
computer-executable program code comprises: (1) a first code portion
configured to access a memory comprising account information stored
therein about a plurality of accounts, the account information comprising
transaction information and exposure information for each of the
plurality of accounts; (2) a second code portion configured to identify a
selected entity; (3) a third code portion configured to identify, from
the transaction information, one or more related entities that are
related to the selected entity; (4) a fourth code portion configured to
gather, from the account information, exposure information for the one or
more related entities; and (5) a fifth code portion configured to
determine a comprehensive view of the exposure to the selected entity
based at least in part on the exposure information of the one or more
related entities.

[0018] The features, functions, and advantages that have been discussed
may be achieved independently in various embodiments of the present
invention or may be combined in yet other embodiments, further details of
which can be seen with reference to the following description and
drawings.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

[0019] Having thus described embodiments of the invention in general
terms, reference will now be made to the accompanying drawings, wherein:

[0020]FIG. 1 provides a block diagram illustrating a comprehensive
exposure analysis system in accordance with an embodiment of the present
invention;

[0021]FIG. 2 provides a flow diagram illustrating a method of performing
a comprehensive exposure analysis in accordance with an embodiment of the
present invention;

[0022]FIG. 3 provides a flow diagram illustrating an example embodiment
of the method of FIG. 2 in which a bank uses its transaction data
associated with a particular company along with exposure metrics of the
company and other bank customers to perform a comprehensive exposure
analysis for the company;

[0023]FIG. 4 provides a flow diagram illustrating a particular method of
performing a comprehensive exposure analysis for a company in accordance
with an example embodiment of the invention;

[0024]FIG. 5 provides a flow diagram illustrating a particular method of
performing a comprehensive exposure analysis for an individual in
accordance with an example embodiment of the invention;

[0025] FIG. 6A provides an exposure analysis interface illustrating an
example chart and graph of an institution's total exposure by sector of
the economy, in accordance with an embodiment of the present invention;

[0026] FIG. 6B provides an exposure analysis interface illustrating an
example chart and graph of an institution's total exposure by industry to
a particular user-selected sector of the economy, in accordance with an
embodiment of the present invention;

[0027] FIG. 6C provides an exposure analysis interface illustrating an
example chart and graph of an institution's total exposure by company to
a particular user-selected industry, in accordance with one embodiment of
the present invention;

[0028]FIG. 7A provides an exposure analysis interface illustrating
example interface controls and an example diagram of an institution's
total exposure for a particular user-selected attribute based on sector,
industry, and company, in accordance with one embodiment of the present
invention;

[0029] FIG. 7B provides an exposure analysis interface illustrating a
geographic chart of an institution's customers that are associated with
(e.g., employees and/or other business partners of) a particular
user-selected company, in accordance with one embodiment of the present
invention;

[0030] FIG. 7C provides an exposure analysis interface illustrating a
chart and graph of an institution's exposures to employees of a
particular user-selected company, in accordance with one embodiment of
the present invention;

[0031] FIG. 8 provides a block diagram illustrating a combined commercial
and consumer credit system and environment, in accordance with an
embodiment of the present invention; and

[0032]FIG. 9 provides a flow diagram illustrating a combined commercial
and consumer credit exposure analysis process, in accordance with one
embodiment of the present invention.

DETAILED DESCRIPTION OF EMBODIMENTS OF THE INVENTION

[0033] Embodiments of the present invention will now be described more
fully hereinafter with reference to the accompanying drawings, in which
some, but not all, embodiments of the invention are shown. Indeed, the
invention may be embodied in many different forms and should not be
construed as limited to the embodiments set forth herein; rather, these
embodiments are provided so that this disclosure will satisfy applicable
legal requirements. Where possible, any terms expressed in the singular
form herein are meant to also include the plural form and vice versa,
unless explicitly stated otherwise. Also, as used herein, the term "a"
and/or "an" shall mean "one or more," even though the phrase "one or
more" is also used herein. Furthermore, when it is said herein that
something is "based on" something else, it may be based on one or more
other things as well. In other words, unless expressly indicated
otherwise, as used herein "based on" means "based at least in part on" or
"based at least partially on." Although some embodiments of the invention
described herein are described as involving a "bank" or "financial
institution," one of ordinary skill in the art will appreciate that other
embodiments of the invention may involve other institutions that take the
place of or work in conjunction with the bank or other financial
institution to perform the described function or maintain the described
system. Like numbers refer to like elements throughout.

[0034] As described briefly above, embodiments of the invention relate
generally to apparatuses and methods for providing a more comprehensive
exposure analysis for an institution. For example, some embodiments of
the invention are configured to analyze the risk exposure that a bank has
to a particular company by virtue of its loan and line of credit
products. When conducting this exposure analysis for the bank,
embodiments of the invention look not only at the loans and lines of
credit extended by the bank to the particular company, but also at the
loans and lines of credit extended to employees, suppliers, contractors,
and/or other business partners of the company to get a more comprehensive
view of the bank's exposure to the company. This type of comprehensive
view of the bank's credit exposure may be more accurate because if the
particular company fails, then the company's employees, suppliers,
contractors, and/or other business partners may also experience financial
hardship that would put the credit extended by the bank to these parties
also at risk. As such, an accurate analysis of the bank's credit exposure
to a particular company should take into account not only the credit
extended to the company, but also at least some portion of the credit
extended to parties that rely on this particular company. Some
embodiments of the invention perform this analysis by, amongst other
things, using information that the bank has about financial transactions
between the company and its business partners to automatically identify
those entities that should be taken into account in the exposure analysis
of the company. For example, some embodiments of the invention provide a
computer system configured to analyze a bank's direct deposit information
for its customers to identify which customers are employees of the
particular company in question and then automatically consider the bank's
exposure to these customers during the exposure analysis of the company.
Some embodiments of the invention are also configured to aggregate the
exposure analysis for all of the companies in a particular sector of the
economy, industry, or geographical area in order to more accurately view
the bank's exposure to the particular sector of the economy, industry, or
geographical area. This paragraph briefly describes just one example of
how embodiments of the invention may be configured to help a bank to more
accurately assess its risk. In another example, embodiments of the
invention identify risks and/or business opportunities for an institution
by analyzing an institution's revenue exposure to a sector of the
economy, industry, geographic area, company, individual, group of
individuals, or other entity or group of entities by, for example, using
transaction data to associate the sector of the economy, industry,
geographic area, company, individual, group of individuals, or other
entity or group of entities with other sectors of the economy,
industries, geographic areas, companies, individuals, groups of
individuals, and/or other entities or groups of entities and combining
their revenue numbers to provide a more accurate picture of the
institution's revenue exposure. These examples and numerous other
examples of embodiments of the invention are described in greater detail
below.

[0035]FIG. 1 provides a block diagram of a comprehensive exposure
analysis system 30, in accordance with an embodiment of the invention. As
illustrated, the comprehensive exposure analysis system 30 includes a
communication interface 40, a memory 60, and a processor 50 communicably
coupled to the communication interface 40 and the memory 60. As used
herein, when it is said that two devices are "communicably coupled" or
"operatively coupled" it means the two devices are coupled by one or more
wired or wireless connections or networks such that one or more
communications can be sent between the devices and/or so that one device
can use the other device to perform one or more operations.

[0036] The communication interface 40 is generally configured to allow the
comprehensive exposure analysis system 30 or components thereof to
communicate with other systems, devices, components, and/or users. In
this regard, as used herein, a "communication interface" generally
includes hardware, and, in some instances, software, that enables a
portion of the system in which it resides, such as the comprehensive
exposure analysis system 30, to transport, send, receive, and/or
otherwise communicate information to and/or from a user and/or the
communication interface of one or more other systems or system devices.
For example, the communication interface 40 of the comprehensive exposure
analysis system 30 may include a network interface and a user interface.
The communication interface 40, and any network interface or user
interface, may be made up of a single device or multiple devices that may
or may not be coupled together. In other words, although a communication
interface 40 is illustrated in FIG. 1 as one block in the block diagram,
the communication interface 40 may comprise one or more separate
systems/devices that perform the functions of the communication interface
40 described herein.

[0037] As used herein, a "network interface" generally includes hardware,
and, in some instances, software, that enables a system or a portion of a
system to transport, send, receive, and/or otherwise communicate
information to and/or from the network interface of one or more other
systems or portions of the system via a network. As used herein, a
"network" is any system for communicating information from one
device/system to another device/system and may include, for example, a
global area network, wide area network, local area network, wireless
network, wire-line network, secure encrypted network, virtual private
network, one or more direct electrical connections, and/or the like. As
such, a network interface may include a wired or wireless modem, server,
electrical connection, and/or other electronic device that communicably
connects one device/system to another device/system on the network and,
in some cases, is configured to communicate using one or more particular
network communication protocols.

[0038] As used herein, a "user interface" generally includes one or more
user output devices, such as a display and/or speaker, for presenting
information to a user. In some embodiments, the user interface further
includes one or more user input devices, such as one or more buttons,
keys, dials, levers, directional pads, joysticks, accelerometers,
controllers, microphones, touchpads, touchscreens, haptic interfaces,
scanners, motion detectors, cameras, and/or the like for receiving
information from a user.

[0039] In the illustrated embodiment, the communication interface 40 is
configured to communicate input from and/or output to a user interface
system 70. The user interface system 70 may be part of the comprehensive
exposure analysis system 30 and, as such, maintained by the same entity
that maintains the comprehensive exposure analysis system 30.
Alternatively, the user interface system 70 may be maintained by an
entity other than the entity that maintains the comprehensive exposure
analysis system 30 and may be, for example, a personal computer, mobile
phone, or other personal user interface device. In either case, the user
interface system 70 may be communicably coupled to the communication
interface 40 via a network, and the user interface system 70 may be
either co-located with or located remote from the other devices of the
comprehensive exposure analysis system 30.

[0040] As also illustrated in FIG. 1, the comprehensive exposure analysis
system 30 is configured to communicate with a transaction data datastore
10, an exposure data datastore 20, and an entity data datastore 25. In
some embodiments of the invention, the transaction data datastore 10, the
exposure data datastore 20, and/or the entity data datastore 25 are
stored on the memory devices of one or more other systems, such as one or
more banking computer systems, which may or may not be maintained by the
same entity maintaining the comprehensive exposure analysis system 30. In
other embodiments, the transaction data 10, exposure data 20, and/or
entity data 25 are stored in memory 60 of the comprehensive exposure
analysis system 30. In embodiments where the transaction data 10, the
exposure data 20, and/or entity data 25 are located in other systems, the
comprehensive exposure analysis system 30 may be configured to
communicate with those systems via a network interface of the
communication interface 40 and a network that, in some embodiments, uses
one or more encryption techniques and/or secure communication protocols
to ensure the confidentiality of the information communicated. In one
embodiment of the invention, the transaction data 10, exposure data 20,
an entity data 25 are obtained from an account information datastore 5
which includes account information (e.g., for bank accounts) for
customers of the institution for which the comprehensive exposure
analysis is being performed.

[0041] The transaction data 10 generally includes any data available to
the institution about any transaction between two or more entities. In
one embodiment, the transaction data includes financial transaction data,
such as information about direct deposit, Automated Clearing House (ACH),
purchase, sale, payment, transfer, deposit, bill-pay, loan, payroll, or
other transaction. For example, in one embodiment of the invention, the
institution conducting for which the comprehensive exposure analysis is
being conducted is a financial institution, such as a bank, and the
transaction data 10 includes information about one or more different
types of transactions in which the financial institution was directly or
indirectly involved.

[0042] The exposure data 20 generally includes information about the
institution's exposure to one or more entities with respect to one or
more different areas. For example, in one embodiment, the exposure
analysis involves an analysis of an institution's credit exposure. As
used herein "credit exposure" relates to the institution's exposure to a
particular entity or group of entities with regard to loans and/or lines
of credit provided or extended to the particular entity, group of
entities, and/or related entities. In such an example, the exposure data
20 may include, for example, the amount of a loan extended to an entity,
the amount of a line of credit extended to an entity, the current balance
of a loan or line of credit, payments due on a loan or line of credit,
payments overdue on a loan or line of credit, interest rates or interest
due on a loan or line of credit, terms lengths of a loan, and/or any
other information about loans or lines of credit and terms thereof. In
another example embodiment, the exposure analysis involves an analysis of
an institution's revenue exposure. As used herein "revenue exposure"
relates to the institution's exposure to a particular entity or group of
entities with regard to revenue received from the particular entity,
group of entities, and/or related entities. In such an example, the
exposure data 20 may include, for example, an amount of revenue or profit
received by the institution from an entity, a percentage of revenue or
profit received by the institution from an entity, information about
revenue or profit received by the institution from an entity overall or
in a particular area of the institution's business (e.g., revenue a bank
receives in interest and/or fees, revenue a bank receives from mortgage
products, revenue a bank receives from consumer deposit accounts, etc.).
The data can include past, current, and/or projected data.

[0043] The entity data 25 generally includes other data that the
institution or system 30 has about one or more entities. For example, the
entities may be customers of the institution and the entity data may
include entity characteristic information such as FICO score,
geographical location(s), household information, age, sex, industry,
sector of economy, credit history, credit score or other rating, product
preferences, other preferences, size in term of employees or financial
characteristics, etc.

[0044] As described above, the comprehensive exposure analysis system 30
includes memory 60. As used herein, "memory" includes any computer
readable medium (as defined herein below) configured to store data, code,
and/or other information. The memory 60 may include volatile memory, such
as volatile Random Access Memory (RAM) including a cache area for the
temporary storage of data. The memory 220 may also include non-volatile
memory, which can be embedded and/or may be removable. The non-volatile
memory can additionally or alternatively include an electrically erasable
programmable read-only memory (EEPROM), flash memory or the like. The
memory 60 may be made up of a single device or multiple devices that may
or may not be coupled together. In other words, although the memory 60 is
illustrated in FIG. 1 as one block in the block diagram, the memory 60
may comprise one or more separate systems/devices that perform the
functions of the memory 60 described herein.

[0045] The memory 60 can store any of a number of applications which
comprise computer-executable instructions/code executed by the processor
50 to implement the functions of the comprehensive exposure analysis
system 30, user interface system 70, and/or other systems described
herein. For example, as illustrated in FIG. 1, the memory 60 may include
an exposure analysis application 65. The exposure analysis application 65
generally includes computer-executable code/instructions for using the
transaction data 10 and/or the exposure data 20 to perform a
comprehensive exposure analysis such as code for instructing the
processor 50 to perform one or more of the functions, steps, or
procedures described in one or more of FIGS. 1-9. The exposure analysis
application 65 may also instructions for presenting a graphical user
interface (GUI) on the display device 72 of the user interface 70 that
allows a user to communicate with the comprehensive exposure analysis
system 30.

[0046] The memory 60 can also store any of a number of pieces of
information/data used or produced by the comprehensive exposure analysis
system 30 and/or the user interface system 70 as well as the applications
and devices that make up the comprehensive exposure analysis system 30
and/or the user interface system 70 to implement the functions of the
comprehensive exposure analysis system 30, the user interface system 70,
and/or other systems described herein. For example, as illustrated in
FIG. 1, the memory 60 generally includes a datastore of comprehensive
exposure metrics 68 generated by the comprehensive exposure analysis
system 30. The memory 60 may also include such data as user preferences
information, user-defined rules, and user selections.

[0047] The comprehensive exposure metrics 68 generally include any
information about the institution's exposure (e.g., in terms of credit,
revenue, or the like) to one or more entities and/or related entities.
For example, the comprehensive exposure metrics 68 may include
information about product use associated with the entity or group of
entities, such as but not limited to the amount or number of deposits,
credit cards, installment loans, lines of credit, mortgages, credit
outstanding, unused lines of credit, and/or the like that are used by the
entity, group of entities, and/or related entities associated with the
entity or group of entities. The comprehensive exposure metrics 68 may
also include information about consumer exposure (e.g., individuals'
exposure), commercial exposure (e.g., company's exposure), combined
commercial and consumer exposure, consumer-commercial ratio,
credit-deposit ratio, total exposure, weighted exposure, etc. The metric
68 may also include aggregated data about the entity, group of entities,
and/or related entities such as number of households, number of
individuals, average FICO score of individuals, geographic distribution
information, geographic density information, Metrics may be aggregated,
weighted, and/or culled for double-counting to present totals by sector,
industry, geographical indicator (e.g., country, region, state, county,
city, town, village, zip code, area code, street, neighborhood, GPS
coordinates, other geocode boundaries, and/or the like), company, group
of companies, individual, group of individuals, product, group of
products, and/or the like. Some example metrics 68 are illustrated in and
described with reference to FIGS. 6A-6C and 7A-7C.

[0048] The processor 50 of the comprehensive exposure analysis system 30,
and any other processors described herein, generally include circuitry
for implementing communication and/or logic functions of the system in
which the processor resides, such as the comprehensive exposure analysis
system 30 and/or the user interface system 70. For example, the processor
50 may include a digital signal processor device, a microprocessor
device, and various analog to digital converters, digital to analog
converters, and/or other support circuits. Control and signal processing
functions of the system are allocated between these devices according to
their respective capabilities. The processor 50, thus, may also include
the functionality to encode and interleave messages and data prior to
modulation and transmission. Further, the processor 50 may include
functionality to operate one or more applications/software programs,
which may be stored in the memory 60, such as the exposure analysis
application 65. The processor 50 may be made up of a single device or
multiple devices that may or may not be coupled together. In other words,
although the processor 50 is illustrated in FIG. 1 as one block in the
block diagram, the processor 50 may comprise one or more separate
systems/devices that perform the functions of the processor 50 described
herein.

[0049] As described in more detail below, the user interface system 70 may
be used to present the comprehensive exposure metrics 68 to a user, as
described in greater detail below. For example, in response to user input
entered through the user interface system 70, certain comprehensive
exposure metrics for certain entities or groups of entities may be
displayed to a user in various ways via the display device 72. For
example, in some embodiments of the invention, the interfaces of FIGS.
7-12 are provided to a user via the display device 72 and the user
interface system 70. The comprehensive exposure metrics 68 may then be
used by the user to assess risk and/or identify business opportunities
that may then prompt action on behalf of the institution. In some
embodiments of the invention, the comprehensive exposure metrics 68 may
then be plugged into another computer system or algorithm of the
comprehensive exposure analysis system 30 in order to automatically take
action based on the metrics and certain pre-defined rules.

[0050]FIG. 2 provides a flow diagram illustrating a method 200 of
performing a comprehensive exposure analysis for an institution in
accordance with an embodiment of the present invention. For example, in
some embodiments of the invention the method 200 is performed by or using
the system 30 described in FIG. 1. In particular, in some embodiments,
the steps of the method 200 are encoded in computer-executable program
code (i.e., computer-readable instructions) of the exposure analysis
application 65 and this code is executed by the processor 50 using, for
example, it's processing components, the communication interface 40, the
memory 60, the datastores 10 and 20, and/or the user interface system 70.

[0051] As illustrated by block 202 in FIG. 2, the method 200 generally
includes selecting an entity. As used herein, the term "entity" refers to
any individual or institution. As used herein, the term "institution"
refers to any company, corporation, business, partnership, organization,
agency, administration, group of individuals, or the like. For example,
in one embodiment of the invention, the method involves the processor 50
selecting an entity by accessing the transaction data 10, exposure data
20, and/or entity data 25 and using the data to select a customer of the
institution for which the exposure analysis is being performed (e.g., a
company or individual that has an account with or uses a product of the
institution). In another embodiment of the invention, the processor 50
selects an entity 202 based on user input received from a user via the
user interface system 70, where the user input includes an indication of
a user-selected entity.

[0052] As illustrated by block 210, the method 200 further involves
determining an institution's exposure to the selected entity in
isolation. In one embodiment of the invention, the processor 50
determines the institution's exposure to the selected entity in isolation
by accessing the exposure data 20 and determining the institution's
direct exposure to the selected entity. For example, where the selected
entity is a company and where the exposure analysis includes an analysis
of the institution's credit exposure to the selected company, the
exposure data 20 may comprise loan and/or line of credit account
information for the institution's customers including the selected
company. In such an example, the processor 50 may look through the
account information to identify all of the current balances for the loans
and/or lines of credit held by the selected company. The processor 50 may
then sum all of the identified balances to obtain a monetary amount
representing the institution's total direct credit exposure to the
selected company. It will be appreciated by one of ordinary skill in the
art that this is just an example and that other ways of calculating
direct credit exposure may vary in other embodiments of the invention.
Furthermore, similar methods may be performed with regard to revenue in
order to calculate direct revenue exposure to the selected company or
other entity.

[0053] As described briefly above, embodiments of the invention also use
transaction data to automatically determine one or more other entities
that are regular business partners (i.e., "related entities") of the
selected entity and then calculate the institution's exposure to the
selected entity based at least partially on the institution's exposure to
these one or more related entities. In this regard, blocks 204-212
illustrate an example of a process for determining related entities and
using these related entities in the exposure analysis of the selected
entity.

[0054] More particularly, as illustrated by block 204, the method 200
includes accessing transaction data associated with the selected entity.
For example, in one embodiment of the invention, the processor 50 access
the transaction data 10 to identify one or more transactions, such as
financial transactions: (1) in which the institution was involved or has
knowledge, and (2) that are transactions between the selected entity and
another entity. Where the selected entity is a company, the transactions
may include, for example, direct deposit transactions or other ACH
transactions since these transactions are often likely to be made with an
employee, supplier, distributor, or other business partner. In some
embodiments, the processor 50 identifies all transactions in the
datastore 10 that involve the selected entity, while in other embodiments
of the invention the processor identifies only those transactions that
are a particular defined type of transaction and/or occur with a certain
pre-determined frequency/regularity.

[0055] As illustrated by block 206, the method 200 then involves using the
transaction data accessed in the process represented by block 204 to
identify related entities that do business with the selected entity. In
some embodiments, this process involves identifying the party opposite
the selected entity in all of the transactions identified in the process
represented by block 204. In other embodiments, this process involves
analyzing the transaction data associated with the selected entity and
identifying only those other "related" entities that perform certain
pre-defined types of transactions that also occur above a pre-defined
frequency threshold. In other words, some embodiments of the invention
analyze the transaction data to only identify as related entities those
entities that rely significantly on the selected entity financially so as
to warrant considering these entities in the exposure analysis of the
selected entity. For example, the rules may be created to attempt to
automatically identify the selected entity's employees, suppliers,
distributors, retailers, manufacturers, customers, employers, affiliates,
and/or other business partners so that these entities can be particularly
included or excluded from the exposure analysis of the institution's
exposure to the selected entity.

[0056] For example, in some embodiments of the invention, the exposure
analysis application 65 has rules defining the requirements of related
entities in one or more contexts. In some embodiments, these rules can be
created or modified by a user of the user interface system 70. In some
embodiments, the rules include transaction type requirements that
instruct the processor 50 to identify those transactions that are of a
particular type and then use those identified transactions to identify
related entities. For example, suppose that the comprehensive exposure
analysis system 30 is being used to conduct a credit exposure analysis
for an institution and, as such, the user desires to identify the
institution's credit exposure to a company that includes an analysis of
the institution's credit exposure to the company's employees. In such an
example, the exposure analysis application 65 may include a rule
instructing the processor 50 to identify the entity on the other end of a
transaction with the selected company, but only if the transaction is a
direct deposit transaction from the company to the entity.

[0057] In some embodiments, the rules include transaction requirements
that instruct the processor 50 to identify those transactions that occur
with a particular frequency and then use those identified transactions to
identify related entities. The frequency may be defined by a number of
overall transactions or by a number of transactions within a particular
period of time. For example, the frequency requirement may instruct the
processor 50 to identify entities as related entities if they transact a
certain type(s) of transaction with the selected entity greater than a
predefined number of times where the predefined number of times may be
any number greater than zero. In another example, the frequency
requirement may instruct the processor 50 to identify entities as related
entities if they transact a certain type(s) of transaction with the
selected entity greater than a predefined number of times within a
predefined time period, where the predefined time period may be a year,
quarter, month, two weeks, week, day, hour, minute, or any other time
period. The frequency requirement may also be defined by a percentage of
the selected entity's transactions and/or of the related entity's
transactions (e.g., related entities may include only those entities that
account for greater than 5% of the selected entity's total transactions).
The frequency requirement may be defined using an integer or percentage
threshold where the processor is instructed to identify those
transactions that occur with a frequency equal to, above, and/or below
the integer or percentage. The frequency requirement may be defined using
an integer or percentage range where the processor is instructed to
identify those transactions that occur with a frequency either inside or
outside the range. Such a threshold or range may be created by a user
using the user interface system 70 or may be dynamically created by the
processor 50 based on the transaction data 10 and certain rules (e.g.,
neural network rules or other artificial intelligence rules) for
dynamically generating the threshold or range. The frequency requirement
may be applied to all transactions with a particular entity to see if the
transactions between a particular entity and the selected entity
generally satisfy the pre-defined frequency requirements, or the
frequency requirement be applied only to those transactions with a
particular entity that are of a particular type and/or size to see if
these particular transactions meet the pre-defined frequency
requirements. For example, in the example where the comprehensive
exposure analysis system 30 is configured to identify the institution's
credit exposure to a company that includes an analysis of the
institution's credit exposure to the company's employees, the exposure
analysis application 65 may include a rule instructing the processor 50
to identify the entity on the other end of a transaction with the
selected company, but only if the transaction is a direct deposit
transaction from the company to the entity and only if the direct deposit
occurs with a frequency equal or greater than once per month.

[0058] In some embodiments, the rules include transaction requirements
that instruct the processor 50 to identify those transactions that are of
a pre-defined size (e.g., are for a pre-defined amount of money) and then
use those identified transactions to identify related entities. The size
requirement may be defined using an integer or percentage threshold where
the processor is instructed to identify those transactions that are of a
size equal to, above, and/or below the integer or percentage. The size
requirement may be defined using an integer or percentage range where the
processor is instructed to identify those transactions that are of a size
either inside or outside the range. Such a threshold or range may be
created by a user using the user interface system 70 or may be
dynamically created by the processor 50 based on the transaction data 10
and certain rules (e.g., neural network rules or other artificial
intelligence rules) for dynamically generating the threshold or range.
The size requirement may be applied to all transactions with a particular
entity to see if any transactions between a particular entity and the
selected entity satisfy the pre-defined size requirements, or the size
requirement may be applied only to those transactions with a particular
entity that are of a particular type and/or frequency to see if these
particular transactions meet the pre-defined size requirements. For
example, in an example where the comprehensive exposure analysis system
30 is configured to identify the institution's credit exposure to a
company that includes an analysis of the institution's credit exposure to
the company's largest suppliers, the exposure analysis application 65 may
include a rule instructing the processor 50 to identify the entity on the
other end of a transaction with the selected company, but only if the
transaction is a payment transaction (e.g., a check or ACH) from the
company to the entity, only if the transaction occurs with a frequency
equal or greater than once per quarter, and only if the transaction is
greater than or equal to two hundred thousand dollars.

[0059] As illustrated by block 208, the method 200 then involves
determining the institution's exposure to each of the related entities
identified in the process represented by block 206. For example, in one
embodiment of the invention, the processor 50 accesses the exposure data
20 and searches for and obtains any exposure data associated directly
with a related entity. Whether there is any relevant exposure data 20
directly associated with the related entity will depend on whether the
related entity is a customer of the institution and, even if the related
entity is a customer, whether the related entity uses any products of the
financial institution relevant to the particular exposure analysis being
performed. In some embodiments of the invention, the processor accessing
the exposure data involves first comparing the related entities to an
overall institution customer list or with a product-specific customer
list before trying to obtain exposure data for a related entity in order
to identify whether there will be any relevant exposure data 20 for the
particular related entity. In other embodiments, the processor 50 could
instead just try to get exposure data for the related entity from the
exposure data datastore 20 and receive a null value if nothing is in the
datastore 20 associated with the particular related entity and/or
relevant to the particular exposure analysis. Once received, the
processor 50 may temporarily store the relevant exposure data of each of
the related entities in memory 60 so as to perform the herein-described
operations on the data.

[0060] In some embodiments, the processor 50 reviews exposure data
associated with each related entity to determine whether the exposure
data is relevant to the particular exposure analysis being performed.
Whether certain exposure data is relevant may depend on the type of data
(e.g., credit or revenue data, etc.) or the type of product (e.g., home
loan, car loan, home equity line of credit, credit card line of credit,
revolving credit, revenue from deposit account, revenue from credit
account, revenue from transaction fees, revenue from late fees, etc.).
Relevancy of exposure data may also depend on other rules, which rules
may or may not be user-defined or user-modifiable. For example, relevancy
may also be based on the size of the exposure (e.g., small exposure below
a particular threshold may be considered negligible or insignificant for
some exposure analyses), the size of the related entity, the size of the
selected entity, the type of related entity, the type of selected entity,
and/or the relationship between the selected entity and the related
entity.

[0061] As illustrated by block 212, the method 200 then involves combining
the exposure data for the selected entity (i.e., the exposure data
determined from the process represented by block 210) and/or the exposure
data for one or more of the related entities (i.e., the exposure data
determined from the process represented by blocks 204-208) to obtain
comprehensive exposure metrics 68 for the selected entity. For example,
the comprehensive exposure metrics 68 may include such metrics as the
total exposure, total weighted exposure, total exposure of all related
entities (e.g., exposure to consumer accounts of all employees of the
selected entity), total exposure of the selected entity, ratio of the
total exposures of the selected and related entities, credit to debit
ratios for these entities or groups of entities, average exposure to
related entities, relative exposure percentages of the entities or groups
of entities, number or percentage of related entities associated with the
selected entity to which the institution is or is not exposed, and/or the
like. In some embodiments, the processor 50 performs the calculations and
stores the comprehensive exposure metrics 68 in the memory 60.

[0062] In some embodiments, the exposure metrics are simply totaled or
averaged across related entities and/or across the related and selected
entities. In other embodiments, the exposure metrics are weighted before
they are totaled or averaged based on the related entity, exposure,
selected entity, number of related entities, and/or relationship between
the selected and related entity. For example, if the selected entity
supplies to a related entity almost all of the related entity's revenue,
then perhaps a loan or line of credit extended to the related entity
should be counted 100% in the credit exposure analysis of the selected
entity because if the selected entity were to fail and default on its
loans, the loans of the related entity, which receives almost all of its
revenue from the selected entity, would very likely also default.
However, in other situations it may be useful to count the exposures to
one or more related entities less relative to other exposures to obtain a
more accurate risk rating for a selected entity.

[0063] In other embodiments when determining the exposure of a selected
entity and the related entities it may be helpful to drill down into the
exposure of secondary related entities. For example, if a related entity
has forty (40) percent of its exposure from the selected entity and the
other sixty (60) percent from other entities (i.e. secondary related
entities) it may be helpful to identify the credit exposure of a related
entity based on the selected entity and secondary related entities.
Therefore, in some embodiments the metrics are tracked for the exposure
of a related entity based on the selected entity and secondary related
entities in the same ways as described herein for tracking the metrics
for the selected entity based on the related entities.

[0064] It should be appreciated that, in some embodiments of the
invention, only the exposure data for the plurality of related entities
are combined together and are not combined with any exposure data of the
selected entity when comprehensive exposure metrics are being generated.
For example, in a product exposure analysis for a bank that is attempting
to view the success of marketing and possible marketing opportunities,
embodiments of the present invention may be used to identify all of the
employees and contractors of a selected company and identify which
percentage of these customers are customers of the bank with regard to a
particular product (i.e., the bank's "product exposure" to the selected
company's employees for a particular product). If the percentage is low,
perhaps the bank could offer a group banking program to the company for
the company to offer as an employee benefit. This may then incentivize
more employees to use banking products. On the other hand, if the
percentage is high, then the bank may want to use its resources to target
other companies or marketing efforts.

[0065] As illustrated by block 216, the method 200 may then involve
displaying or otherwise using the comprehensive exposure metrics obtained
from the process represented by block 212. In some embodiments of the
invention, the exposure analysis application 65 includes
computer-executable program code for a graphical user interface (GUI)
that the processor 50 communicates, via the communication interface 40,
to the display device 72 of the user interface system 70. For example,
FIGS. 6C, 7B, and 7C illustrate example user interfaces that present
example comprehensive exposure metrics for a selected entity.

[0066] As illustrated in FIG. 2, in some embodiments of the method 200,
the process represented by blocks 202-212 may be repeated for numerous
different entities to obtain comprehensive exposure metrics 68 for each
of the different selected entities. As illustrated by block 214, in some
such embodiments, the method 200 further involves aggregating the
comprehensive exposure metrics 68 for several of the different selected
entities based on entity characteristics to create other exposure metrics
68. Examples of entity characteristics include, for example, but are not
limited to, the sector of the economy in which the entity exists, the
industry type of the entity, the geographical location(s) of the entity,
and/or the like. Entity characteristics may be determined from the entity
data datastore 25. Embodiments of the invention could include weighting
or exclusion methods that could avoid double counting of the
institution's exposure to related entities where the related entities are
related to a number of different entities being summed together. In other
embodiments, however, entities and the exposure thereto may be double
counted in the aggregations.

[0067] As illustrated by block 216, the method 200 may then involve
displaying or otherwise using the exposure metrics generated from the
process represented by block 214. For example, FIGS. 6A-7C illustrate
example user interfaces that present example comprehensive exposure
metrics for a groups of selected entities.

[0068] Once the metrics are created, they may be acted on by the
institution to affect marketing, underwriting, reporting, strategizing,
and/or the like. In some embodiments of the invention, the comprehensive
exposure metrics 68 may be automatically communicated by the
comprehensive exposure system 30 to one or more other such decision
making systems where automated and/or manual decisions may be made based
thereon.

[0069]FIG. 3 provides a flow diagram illustrating an example embodiment
300 of the method 200 of FIG. 2. In this example embodiment 300, a bank
uses its transaction data associated with a particular company along with
exposure metrics of the company and other bank customers to perform a
comprehensive exposure analysis regarding the bank's exposure to the
company. However, it will be understood in view of this disclosure that
FIG. 3 is just a mere example of the process with respect to FIG. 2 and
that the description of FIG. 2 is not limited by the description of FIG.
3.

[0070] In some embodiments of the invention, the method 300 is performed
by or using the system 30 described in FIG. 1. In particular, in some
embodiments, the steps of the method 300 are encoded in
computer-executable program code (i.e., computer-readable instructions)
of the exposure analysis application 65 and this code is executed by the
processor 50 using, for example, it's processing components, the
communication interface 40, the memory 60, the datastores 10 and 20,
and/or the user interface system 70.

[0071] As illustrated by block 302 in FIG. 3, the method 300 generally
includes selecting a company. For example, in one embodiment of the
invention, the method involves the processor 50 selecting a company by
accessing the transaction data 10, exposure data 20, and/or entity data
25 associated with the bank's commercial accounts and using the data to
select a commercial customer of the bank (e.g., a company that has an
account with or uses a product of the bank). In another embodiment of the
invention, the processor 50 selects a company based on user input
received from a user via the user interface system 70, the user input
including a user-selected company.

[0072] As illustrated by block 310, the method 300 further involves
determining the bank's exposure (e.g., credit exposure metrics, risk
metrics, revenue metrics, business opportunity metrics, etc.) associated
directly with the company itself. In one embodiment of the invention, the
processor 50 determines the bank's exposure to the selected company in
isolation by accessing the exposure data 20 and determining the bank's
direct exposure to the selected company. For example, where the selected
entity is a company and where the exposure analysis includes an analysis
of the bank's credit exposure to the selected company, the exposure data
20 may comprise loan and/or line of credit account information for the
bank's customers including the selected company. In such an example, the
processor 50 may look through the account information to identify all of
the current balances for the loans and/or lines of credit held by the
selected company. The processor 50 may then sum all of the identified
balances to obtain a monetary amount representing the bank's total direct
credit exposure to the selected company. It will be appreciated by one of
ordinary skill in the art that this is just an example and that other
ways of calculating direct credit exposure may vary in other embodiments
of the invention. Furthermore, similar methods may be performed with
regard to revenue to calculate direct revenue exposure to the selected
company or other entity.

[0073] As illustrated by block 304, the method 300 includes accessing the
bank's deposit data, payroll data, ACH data, and/or other transaction
data associated with the selected company. For example, in one embodiment
of the invention, the processor 50 accesses the transaction data 10 to
identify one or more transactions, such as financial transactions, in
which the institution was involved or otherwise has knowledge of and that
are transactions between the selected company and another entity. In some
embodiments, the processor 50 identifies all transactions in the
datastore 10 that involve the selected company, while in other
embodiments of the invention the processor identifies only those
transactions that are a particular defined type of transaction and/or
occur with a certain frequency/regularity. In some embodiments of the
invention, the transaction data is obtained from the selected company's
account with the bank. In other embodiments, however, the transaction
data is obtained from other customers' accounts where the transactions
are between those customers and the selected company. As such, even if a
selected company is not a customer of the bank, some embodiments of the
invention can still analyze the bank's exposure to the selected company
by virtue of the bank's exposure to related companies that may rely on or
do business with the selected company.

[0074] As illustrated by block 306, the method 300 then involves using the
transaction data to identify employees, consumers, suppliers, business
partners, company customers, bank customers, and/or other entities that
do business with the selected company. As illustrated by block 308, the
method 300 then involves determining the bank's exposure to each of the
related entities identified in the process represented by block 306.

[0075] As illustrated by block 312, the method 300 then involves combining
the exposure data for the selected company (i.e., the exposure data
determined from the process represented by block 310) and/or the exposure
data for one or more of the related entities (i.e., the exposure data
determined from the process represented by blocks 304-308) to obtain
comprehensive exposure metrics 68 for the selected company. As
illustrated in FIG. 3, in some embodiments of the method 300, the process
represented by blocks 302-312 may be repeated for numerous different
companies to obtain comprehensive exposure metrics 68 for each of the
different selected companies. As illustrated by block 314, in some such
embodiments, the method 300 further involves aggregating the
comprehensive exposure metrics 68 for several of the different selected
companies based on entity characteristics to create other exposure
metrics 68. Examples of entity characteristics include, for example, but
are not limited to, the sector of the economy in which the company
exists, the industry type of the company, the geographical location(s) of
the company, and/or the like. Embodiments of the invention could include
weighting or exclusion methods that avoid double counting of the bank's
exposure to related entities where the related entities are related to a
number of different companies being summed together. In other
embodiments, however, entities and the exposure thereto may be double
counted in the aggregations.

[0076] As illustrated by block 316, the method 300 may then involve
displaying the exposure metrics 68 resulting from the process represented
by block 312 and/or 314 to a user via the user interface system 70,
inputting the exposure metrics into a computerized decisioning system via
the communication interface 40, or otherwise using the exposure metrics
68 to identify and manage business opportunities and/or risks for the
bank. For example, FIGS. 6A-7C illustrate example user interfaces that
present example comprehensive exposure metrics for a groups of selected
companies.

[0077]FIG. 4 provides a flow diagram illustrating a particular method 400
of performing a comprehensive exposure analysis for a company in
accordance with an example embodiment of the invention. As illustrated by
block 402, a bank (or other financial institution) develops a
relationship with the company. For example, the company may open a
business account with the bank or hire the bank to manage or process
certain of its financial transactions.

[0078] As illustrated by block 404, the bank's computer systems process
direct deposits, other ACHs, checks, payments, payroll, and/or other
transactions for the company when the company pays employees, suppliers,
distributors, or other business partners and/or when the company is paid
by customers, distributors, and/or other business partners. In some
embodiments, the transactions are electronic transactions and the
transaction information is automatically stored in memory of the bank's
computer systems. In other embodiments, the transactions may not be
electronic, but electronic information about the transactions may be
created and then stored in the memory of the bank's computer systems.
Transaction information may include information about the other entity
(e.g., the payor or payee) opposite the company in the transaction. Such
information may include identifying information such as a name, address,
account number, payment device number, and/or other identifier for the
entity opposite the company. Transaction information may also include
information about the transaction including financial information, such
as amount, currency, payment terms, etc., and non-financial information,
such as descriptions of goods or services being transferred, description
of transaction, type of transaction, date of transaction, and/or the
like. This transaction data is stored and associated with the company in
the memory of the bank's computer system.

[0079] As illustrated by block 406, the bank's computer systems (such as
the system described with reference to FIG. 1) then use the company's
transaction data to determine account numbers or other identifiers for
entities receiving regular payments from the company and/or providing
regular payments to the company. As represented by block 408, based on
the transaction data of the identified entities, the bank's computer
systems then determine the relationship between each identified entity
and the company (e.g., if entities are employees, suppliers,
distributors, key customers, etc., of the company). For example, where an
individual (e.g., a consumer account customer of the bank) receives
repeated payments from the company every week, two weeks, bi-monthly, or
monthly and the amount is within a particular range and rarely varies or
varies only slightly within a small range, then the entity may be
determined by the system to be an employee of the company.

[0080] As represented by block 410, the bank's computer systems then
associate financial characteristics of the identified entities with the
company and/or associate the financial characteristics of the company
with the identified entities for exposure analysis purposes based on the
determined relationship. For example, loans and lines of credit that the
bank has extended to the company's employees may be at least partially
counted or viewed in the bank's analysis of its exposure to the company
overall. The bank's exposure to the company may also be considered when
analyzing the bank's exposure to the individual. In some embodiments,
weighting factors are used to reduce or increase the weight of the bank's
exposure to each related entity or group of related entities relative to
the weight put on the company's own exposure or the weight put on other
related entities or groups of entities. These weighting factors may be
based on the type of relationship between the company and the related
entity, as well as on the type of exposure.

[0081]FIG. 5 provides a flow diagram illustrating a particular method 500
of performing a comprehensive exposure analysis for an individual in
accordance with an example embodiment of the invention. As illustrated by
block 502, the bank develops a relationship with an individual (i.e., a
"consumer") by the individual opening a financial account with the bank.
For example, the individual may open a consumer account with the bank or
have a credit account with the bank by virtue of a loan or line of credit
owned or managed by the bank.

[0082] As illustrated by block 504, the bank's computer systems process
direct deposits, other ACHs, checks, payments, payroll, and/or other
transactions for the individual when the individual regularly receives
payment from entities (e.g., employers) and/or regularly makes payments
to other entities. In some embodiments, the transactions are electronic
transactions and the transaction information is automatically stored in
the memory of the bank's computer systems. In other embodiments, the
transactions may not be electronic, but electronic information about the
transaction may be created and then stored in the memory of the bank's
computer systems. Transaction information may include information about
the other entity (e.g., the payor or payee) opposite the individual in
the transaction. Such information may include identifying information
such as a name, address, account number, payment device number, and/or
other identifier for the entity opposite the individual. Transaction
information may also include information about the transaction including
financial information, such as amount, currency, payment terms, etc., and
non-financial information, such as descriptions of goods or services
being transferred, description of transaction, type of transaction, date
of transaction, and/or the like. This transaction data is stored and
associated with the individual in the memory of the bank's computer
system.

[0083] As illustrated by block 506, the bank's computer systems (such as
the system described with reference to FIG. 1) then use the individual's
transaction data to determine account numbers or other identifiers for
entities receiving regular payments from the individual and/or providing
regular payments to the individual. As represented by block 508, based on
the transaction data of the identified entities, the bank's computer
systems then determine the relationship between each identified entity
and the individual (e.g., if entities are employers, employees,
suppliers, service providers, etc., of the individual). For example,
where an individual (e.g., a consumer account customer of the bank)
receives repeated payments from an entity every week, two weeks,
bi-monthly, or monthly and the amount is within a particular range and
rarely varies or varies only slightly within a small range, then the
entity may be determined by the system to be an employer of the
individual.

[0084] As represented by block 510, the bank's computer systems then
associate financial characteristics of the identified entities with the
individual and/or associate the financial characteristics of the
individual with the identified entities for exposure analysis purposes
based on the determined relationship. For example, loans and lines of
credit that the bank has extended to the individual may be at least
partially counted or viewed in the bank's analysis of its exposure to the
individual's employer because the employer failing would also put the
loans given to employees at greater risk of default. The bank's exposure
to the employer may also be considered when analyzing the bank's exposure
to the individual. In some embodiments, weighting factors are used to
reduce or increase the weight of the bank's exposure to each related
entity or group of related entities relative to the weight put on the
individual's own exposure or the weight put on other related entities or
groups of entities. These weighting factors may be based on the type of
relationship between the individual and the related entity, as well as on
the type of exposure.

[0085] FIG. 6A provides an exposure analysis interface 600 illustrating an
example chart and graph of a financial institution's total exposure to a
particular user-selected sector of the economy, in accordance with an
embodiment of the present invention. FIG. 6A illustrates a breakdown of
the financial institution's consumer credit exposure 602 (financial
institution's exposure to individuals with consumer accounts that are
related to businesses in the sector), the commercial credit exposure 604
(financial institution's exposure to businesses with commercial accounts
that are related to businesses in the sector), the combined credit
exposure 606, consumer-commercial exposure ratio 608, and credit-deposit
ratio 610, for various sectors listed in the sector column 612. As
illustrated in FIG. 6A, Company A is part of the industrials sector. The
exposure analysis interface 600 illustrates that the consumer credit
exposure 602 for the industrials sector is approximately six billion
dollars and the commercial credit exposure 604 of the industrials sector
is approximately ten billion dollars, for a total credit exposure 606 of
approximately sixteen billion dollars. These comprehensive exposure
metrics 68 indicate that the financial institution is heavily exposed to
industrials with regard to credit (i.e., loans and lines of credit) that
it extends. A user can utilize this information to illustrate that the
financial institution may want to try to increase its exposure in the
consumer side of the industrials sector, or that it might be better to
increase revenue and risk in another sector, such as the health care,
energy, or information technology sectors, because the financial
institution is already heavily leveraged in the industrials sector. The
consumer-commercial credit exposure ratio 608 and the credit-deposit
ratio 610 are other examples of comprehensive exposure metrics 68 that
can also be used to evaluate whether the financial institution is over or
under exposed.

[0086] FIG. 6B provides an exposure analysis interface illustrating an
example chart and graph of an institution's total credit exposure by
industry to a particular user-selected sector of the economy, in
accordance with an embodiment of the present invention. FIG. 6B
illustrates the same breakdown of the consumer credit exposure 602, the
commercial credit exposure 604, the combined credit exposure 606,
consumer-commercial credit exposure ratio 608, and credit-deposit ratio
610, but it relates to the specific industries within a sector chosen by
a user from the list of sectors illustrated in FIG. 6A. For example, in
the aerospace and defense industry of the industrials sector, the
consumer credit exposure is almost three billion dollars, while the
commercial exposure is only approximately seven-hundred million dollars
for a combined approximate three and one-half billion dollars of
exposure. Therefore, there is may be an opportunity to increase the
commercial exposure in the aerospace and defense industry, or increase
exposure in other industries within the industrials sector that have a
lower total combined exposure 606, such as trading companies, or air
freight and logistics, or a lower credit-deposit ratio 610.

[0087] FIG. 6C provides an exposure analysis interface illustrating an
example chart and graph of an institution's total exposure by company to
a particular user-selected industry, in accordance with one embodiment of
the present invention. Specifically, FIG. 6C illustrates a chart and
graph of the total exposure by company in the aerospace and defense
industry, which may have been selected by a user from the interface of
FIG. 6B. FIG. 6C illustrates the same comprehensive exposure metrics 68
of the consumer credit exposure 602, the commercial credit exposure 604,
the combined credit exposure 606, consumer-commercial credit exposure
ratio 608, and credit-deposit ratio 610, but it relates to the specific
commercial customers within an industry. For example, Company B has
approximately two and one-half billion dollars in combined credit
exposure, while Company A has approximately nine-hundred million dollars
in combined exposure. Therefore, some users may identify that perhaps
they should have a marketing campaign or offer group banking discounts to
Company A employees because they can afford greater consumer credit risk
amongst this population. The pie graphs 620, 622, and 624 in FIGS. 6A-6B
can illustrate a number of metrics; however, in the illustrated
embodiment the pie graphs illustrate the percentages of the exposure for
each sector, each industry in the sector, and each commercial customer in
the industry, as the case may be.

[0088]FIG. 7A provides an exposure analysis interface illustrating
example interface controls and an example diagram of an institution's
total exposure for a particular user-selected attribute based on sector,
industry, and company, in accordance with one embodiment of the present
invention. The attribute chart 710 illustrates graphically the exposure
of the bank to related consumer customers (e.g., employees and/or
individual contractors) of commercial customers based on various
attributes of the bank's consumer exposure. The user can change the
attribute displayed by selecting a different attribute in the select
attribute section 712. The attributes can include, but are not limited to
household count (i.e., the number of households represented by the
related consumer customers), employee head count, deposit balance, credit
card balances outstanding, installment loan balances outstanding, lines
of credit balances outstanding, mortgage loan balances outstanding, other
credit balances outstanding, unused lines of credit available, other
unused credit available, and total consumer exposure, as is illustrated
by the attribute selection section 712 in FIG. 7A. FIG. 7A can be
utilized by the user in order to identify sectors, industries, and
commercial customers that may have associated risks or revenue
opportunities for related consumers based on specific attributes of the
consumers. For example, if Company Y in the aerospace and defense
industry and the industrials sector is having financial difficulties,
then the user can use the comprehensive exposure analysis system 30, and
specifically the attribute chart, illustrated in FIG. 7A, to identify the
exposure the bank has to related consumers of Company Y. For example,
based on the total exposure attribute chart 710, Company Y has the
largest exposure of total consumer exposure out of all of the other
commercial customers. Therefore, if Company Y is performing poorly, it
increases the total risk to bank more than if Company Z was performing
poorly because of the large related consumer exposure of Company Y. The
related consumers would be a higher risk to default if Company Y was
having financial difficulties, because some of the related consumers
might be affected by the layoffs or reductions in pay. FIG. 7A, also
helps the bank identify areas to increase and reduce loans made to
consumers or to increase or reduce marketing efforts for other financial
products. For example, the bank may want to reduce the amount of loans
provided to the aerospace and defense industry and instead increase other
areas of consumer exposure by marketing loans to other consumers who work
for companies in other industries and sectors that do not have as much
consumer exposure, such as but not limited to in this case, the health
care industry, or energy industry.

[0089] FIG. 7B provides an exposure analysis interface illustrating a
geographic chart 720 of the bank's customers that are associated with
(e.g., employees and/or other business partners of) a particular
user-selected company, in accordance with one embodiment of the present
invention. The geographic location chart 720 illustrated in FIG. 7B
displays the banks exposure to related consumer customers geographically
by state 722 within the United States, and areas within the states 724.
For example, FIG. 7B illustrates the area in which the consumer customer
exposure is the greatest and the least for Company A. For example, the
bank is already heavily exposed to related consumers for Company A in
California and less exposed in Washington. While this often illustrates
where the majority of the population who works for Company A is located,
it can also indicate areas of geographic location that the bank needs to
work on expanding. For example, if the bank knows that there are a large
number of employees located in Texas that work for Company A, but the
geographic location chart 620 illustrates that Texas has a small amount
of consumer exposure, the bank knows it needs to work on creating more
consumer exposure in Texas. As previously described, the geographic
location chart can illustrate the related consumer exposure by country,
region, state, county, city, zip code, street address, etc. in other
embodiments of the invention. Other available information can also be
displayed with the exposure concentration information, such as the
concentration of non-customer consumers related to the selected company
(e.g., non-customer employees of the selected company).

[0090] FIG. 7C provides an exposure analysis interface illustrating a
chart and graph of an institution's exposures to employees of a
particular user-selected company, in accordance with one embodiment of
the present invention. More particularly, FIG. 7C provides a zip code
chart 730 and graph 732 of the exposure of the bank for various
attributes of related consumers of a commercial customer in a particular
geographic location. In one embodiment of the invention illustrated in
FIG. 7C, the related consumer information is summarized for the
commercial customer based on a zip code location. The zip code chart 730,
in one embodiment, illustrates attributes, such as, but not limited to,
the average credit score (FICO score) of related consumers, the number of
related consumer households, the total deposits for related consumers,
total credit card debt of related consumers, total installment loans of
related consumers, total lines of credit of related consumers, total
mortgage balances of related consumers, total credit outstanding of
related consumers, total unused lines of credit available to related
consumers, and the bank's total credit exposure to related consumers of
the commercial customer in the specific geographic region.

[0091] The graph 732, in the illustrated embodiment displays the FICO
distribution for a zip code location. If a user selects another
attribute, the graph 732 changes to display the distribution for the
selected attribute. In some embodiments, the information in the zip code
chart 730 and graph 732 may be summarized by country, region, state,
county, city, and/or the like instead of zip code. In some embodiments,
the information may be summarized not only for related consumers of a
commercial customer, as illustrated in FIG. 7C, but for multiple
commercial customers, such as for related commercial customers in
specific industries, multiple industries, specific sectors, or multiple
sectors.

[0092] Embodiments of the invention also provide systems and methods for
performing exposure analysis and/or other types of analysis for a bank or
other financial institution by automatically determining the interplay
between the consumer side of the bank (i.e., the accounts and other
financial products provided by the bank to individuals) and the
commercial side of the bank (i.e., the accounts and other financial
products provided by the bank to businesses) with regard to the
particular analysis being performed. FIG. 8 illustrates a particular
embodiment of a combined commercial and consumer system and environment
800 in accordance with an embodiment of the present invention. It will be
appreciated that FIG. 8 illustrates only one possible embodiment of the
invention and that other embodiments of the invention may be structured
in different ways. Nothing in FIG. 8 or 9 are intended to limit the
invention described above with reference to FIGS. 1-7 unless specifically
recited in the claims.

[0093] As illustrated in FIG. 8, in this example embodiment, a bank's
credit exposure server 804 is operatively coupled, via a network 802 to
the bank's one or more commercial credit servers 806, one or more
consumer credit servers 808, and one or more user computer systems 805.
In this way, the credit exposure system 810 can receive and send
information from and to the commercial exposure system 820, consumer
exposure system 830, and user computer system 805. In some embodiments of
the invention, the user 803 is an employee of the bank using the credit
exposure system 810. However, in other embodiments of the invention the
user 803 is an agent, contractor, or other person designated to act on
behalf of the bank. The network 802 may be a global area network (GAN),
such as the Internet, a wide area network (WAN), a local area network
(LAN), or any other type of network or combination of networks. The
network 802 may provide for wireline, wireless, or a combination of
wireline and wireless communication between devices on the network.

[0094] As illustrated in FIG. 8, the credit exposure system 810 is located
on the bank credit exposure server 804 and generally comprises a
communication interface 812, a processor 814, and a memory 816. The
processor 814 may include functionality to operate one or more software
programs based on computer-readable instructions thereof, which may be
stored in the memory 816.

[0095] The processor 814 is operatively coupled to the communication
interface 812, and the memory 816. The processor 814 uses the
communication interface 812 to communicate with the network 802 and other
devices on the network 802, such as, but not limited to, the commercial
credit servers 806, consumer credit servers 808, and the user computer
systems 805. As such, the communication interface 812 generally comprises
a modem, server, or other device for communicating with other devices on
the network 802.

[0096] As further illustrated in FIG. 8, the credit exposure system 810
comprises computer-readable instructions 818 stored in the memory 816,
which in one embodiment includes the computer-readable instructions 818
of a combined credit exposure application 817. In some embodiments, the
memory 816 includes a datastore 819 for storing data related to the
credit exposure system 810, including but not limited to data created
and/or used by the combined credit exposure application 817.

[0097] The combined credit exposure application 817 generally provides a
user 803 the ability to identify, receive, generate, view, and analyze a
consolidated picture of exposure risk and/or revenue of a bank based on
the bank's exposure to a customer, as well as the bank's exposure to
related customers. The consolidated picture of exposure can include but
is not limited to consumer exposure, consumer risk rating (FICO),
commercial exposure, commercial risk rating, cross-sectional views based
on company, sector, industry, geography, supplemental risk, and/or the
like for a particular point in time or for a particular point in time as
a function of the difference with a previous point in time. For example,
the consolidated picture of exposure can include the exposure today based
on the exposure yesterday, last week, last month, last quarter, last
year, etc., thus illustrating an improvement or decay in the exposure
over time. In some embodiments of the invention, the risk and/or revenue
exposure is based on a customer that is a commercial customer and the
related bank customers that use products at the bank. However, in other
embodiments, it is to be understood that the risk and/or revenue exposure
could be based on a consumer, a group of consumers, a group of commercial
customers, or one or more combinations of consumers and commercial
customers, as well as the related customers to each, which use products
at the bank. The consolidated picture of the combined consumer and
commercial exposure allows the user 803 at the bank to provide more
effective risk management, consumer lending, commercial lending,
investment banking, and/or the like by spreading risk and/or identifying
areas in various commercial customers, sectors, industries, geographies,
etc., that are under-supported or over-supported by the bank.

[0098] As further illustrated in FIG. 8, the commercial exposure system
820 is located on the commercial credit servers 806. The commercial
exposure system 820 generally comprises a communication interface 822, a
processor 824, and a memory 826. The processor 824 is operatively coupled
to the communication interface 822 and the memory 826. The processor 824
uses the communication interface 822 to communicate with the network 802,
and other devices on the network 802, such as, but not limited to, the
bank credit exposure server 804, consumer credit server 808, and the user
computer systems 805. As such, the communication interface 822 generally
comprises a modem, server, or other device(s) for communicating with
other devices on the network 802.

[0099] As illustrated in FIG. 8, the commercial exposure system 820
comprises computer-readable program instructions 828 stored in the memory
826, which in one embodiment includes the computer-readable instructions
828 of a commercial exposure application 840. In some embodiments, the
memory 826 includes a datastore 829 for storing data related to the
commercial exposure system 820, including but not limited to data created
and/or used by the commercial exposure application 840.

[0100] The commercial exposure application 840 captures and stores
information related to the commercial products provided by the bank to
commercial customers and related commercial customers. The information
includes, but is not limited to, the outstanding balance, payment
schedule, term, account number, identification number, account holder,
etc. for products, such as but not limited to, commercial business loans,
commercial property loans, and other debt instruments for commercial
customers and related commercial customers. In some embodiments of the
invention, the commercial exposure application 840 can receive
information from other servers and systems that capture and store
information related to commercial products offered by the bank. In some
embodiments of the invention, the commercial exposure application 840 is
a part of the combined credit exposure application 817, and can receive
information from other systems and servers related to products offered by
the bank to commercial customers and related commercial customer directly
from the other systems and servers located within and outside of the
bank.

[0101] As further illustrated in FIG. 8, the consumer exposure system 830
is located on the consumer credit servers 808. The consumer exposure
system 830 generally comprises a communication interface 832, a processor
834, and a memory 836. The processor 834 is operatively coupled to the
communication interface 832 and the memory 836. The processor 834 uses
the communication interface 832 to communicate with the network 802, and
other devices on the network 802, such as, but not limited to, the bank
credit exposure server 804, commercial credit server 806, and the user
computer systems 805. As such, the communication interface 832 generally
comprises a modem, server, or other device(s) for communicating with
other devices on the network 802.

[0102] As illustrated in FIG. 8, the consumer exposure system 830
comprises computer-readable program instructions 838 stored in the memory
836, which in one embodiment includes the computer-readable instructions
838 of a consumer exposure application 860. In some embodiments, the
memory 836 includes a datastore 839 for storing data related to the
consumer exposure system 830, including but not limited to data created
and/or used by the commercial exposure application 860.

[0103] The consumer exposure application 860 captures and stores the
information related to the consumer products provided by the bank to
consumers and related consumers. The information includes, but is not
limited to, the outstanding balance, payment schedule, term, account
number, identification number, account holder, etc. for products, such as
but not limited to personal loans, mortgages, lines of credit, school
loans, and other debt instruments for consumers and related consumers. In
some embodiments of the invention, the consumer exposure application 860
can receive information from other servers and systems that capture and
store information related to consumer products offered by the bank. In
some embodiments of the invention the consumer exposure application 860
is a part of the combined credit exposure application 817 and can receive
information from other systems and servers related to products offered by
the bank to consumers and related consumers directly from various systems
and servers located within and outside of the bank.

[0104] The user computer systems 805 have devices that are the same or
similar to the devices described for the credit exposure system 810,
commercial exposure system 820, and consumer exposure system 830 (i.e.
communication interface, processor, memory with computer-readable
instructions, datastore, etc.). Thus, the user computer systems 805 will
communicate with the credit exposure system 810, the commercial exposure
system 820, and consumer exposure system 830 in the same or similar way
as previously described with respect to each. The user computer systems
805 may have a display, camera, keypad, mouse, keyboard, microphone,
and/or speakers for communicating with one or more users 803. In this
way, the user 803 can utilize the credit exposure application 817 to view
and use the combined credit exposure interfaces, which may include those
interfaces such as those illustrated in FIGS. 6 and 7.

[0105] It should be appreciated that, although FIG. 8 illustrates a
separate credit exposure system 810, commercial exposure system 820,
consumer exposure system 830, and user computer system 805, in some
embodiments of the invention the separation between one or more of these
systems is merely conceptual and, in reality, one or more of the hardware
and/or software components described with regard to each system may be
combined and/or shared by two or more of these systems. In other
embodiments, however, the separation is real and not conceptual with
regard to one or more of these systems.

[0106]FIG. 9 illustrates a combined credit exposure process 900 in
accordance with one embodiment of the present invention. First the
combined credit exposure application 817, at the direction of the user
803, or in other embodiments automatically, communicates with the
commercial exposure system 820, in order to identify exposure information
related to the credit exposure of one or more customers, such as a
commercial customer, and receives the information from the commercial
exposure application 840, as illustrated by block 902 in FIG. 9. In some
embodiments of the invention, the user 803 is gathering information
related to a specific company or groups of companies in order to identify
the loan exposure to a specific company or groups of companies. For
example, in one embodiment, the bank can gather information related to a
specific company that uses the bank for products, such as Company A as
illustrated in FIGS. 6A-6C, where Company A is, for example, part of the
industrials sector in the aerospace and defense industry.

[0107] In some embodiments of the invention, as illustrated in block 904
the combined credit exposure application 817 identifies any consumer
transactions the customer has made with consumers. For example, Company
A's accounts are debited whenever they make a payment, such as a payroll
direct deposit into the account of an employee of Company A. The credit
exposure application 817 can receive from the commercial exposure system
820 (or other commercial banking systems and servers at the bank) all the
payments Company A made to consumers. For example, in the case of the
direct deposit of payroll, the bank can identify each employee that works
for Company A by identifying all the payroll payments Company A made to
consumers. The combined credit exposure application 817 captures
identification information about the consumers. In some embodiments of
the invention, due to right to privacy laws the bank does not identify
the consumers by name, however, the bank can capture non-descriptive
identification information of the consumers. The non-descriptive
information can include, but is not limited to, identification numbers,
addresses, payment amounts, account numbers, and/or the like. In other
embodiments of the invention, it may be necessary and/or legal to
identify the consumers though the use of a descriptive identification,
such as the consumers' names, social security numbers, tax information,
etc.

[0108] As illustrated by block 906, in some embodiments of the invention,
the combined credit exposure application 817 communicates with the
consumer exposure system 830 and uses the identification information
(non-descriptive or descriptive) identified in block 904 to determine how
many consumers have a relationship with the bank, and thus can be
classified as related bank customers. For example, in the case of Company
A, the credit exposure application 817 will match up any consumers that
received a payment from Company A that were identified as employees, and
cross-reference those consumers with accounts at the bank to see if the
consumers use any products at the bank. In some embodiments, the payments
made by Company A to consumers are deposited into accounts the consumers
have with the bank. However, in other embodiments the payments made by
Company A are deposited into accounts at other financial institutions,
but the combined credit exposure application 817 can identify if the
consumers that received payments from Company A have other accounts at
the bank through the identification information captured in block 904.

[0109] Once the consumers are identified as related consumers the combined
credit exposure application 817 can identify related consumer information
such as consumer relationship information and consumer account
information from the consumer exposure system 830 (or other systems and
servers that store consumer information and are accessed over the network
802), as illustrated by block 908. The relationship information captured
by the combined credit exposure application 817 can include, but is not
limited to, the number of related consumers who utilize products offered
by the bank, related consumer geographic location information (country,
region, state, county, city, zip code, street address, etc.), credit
score of related consumers, etc. The consumer account information can
include, but is not limited to the amount of deposits, credit card
balances, installment loans, lines of credit, mortgages, outstanding
credit, unused lines of credit, and total consumer exposure (i.e. sum of
the balances and loans) that the related consumers have with the bank. In
some embodiments of the invention, the credit exposure application 817
communicates with other systems and servers at the bank, or outside of
the bank, through the network 802 in order to capture information, such
as, but not limited to the related consumer's credit score from a credit
rating agency, etc.

[0110] In some embodiments of the invention the combined credit exposure
application 817 can also determine the exposed risk and revenue for any
related commercial customers. As illustrated by block 910, the combined
credit exposure application 817 can identify the suppliers, (outbound
transactions), distributors (inbound transactions), partners (inbound and
outbound transactions) of the customer through payment transactions
captured by the commercial exposure system 820 (or other system or server
at the bank), such as wire transfers through automated clearing houses,
deposited checks, or other transaction processes. For example, the
combined credit exposure application 817 can identify all the suppliers,
distributors, and partners of Company A by identifying the transactions
Company A has made with other companies. As previously described with
respect to the consumers, the credit exposure application 817 captures
the commercial identification information (non-descriptive or
descriptive), such as, but not limited to, address, payment information,
account numbers, commercial customer identification numbers, commercial
customer name, tax identification number, etc., of all of the commercial
customers that have been involved in transactions with the customer.

[0111] As illustrated by block 912, in some embodiments of the invention,
the combined credit exposure application 817 communicates with the
commercial exposure system 820 and uses the commercial identification
information (non-descriptive or descriptive) identified in block 910 to
determine how many companies that were involved in transactions with the
customer have a relationship with the bank, and thus can be classified as
related commercial customers. For example, in the case of Company A, the
credit exposure application 817 will match up any companies that were
involved in transactions with Company A, and cross-reference those
companies with accounts at the bank to see if the companies use any
products at the bank, through the use of the commercial identification
information. In some embodiments, the payments made between Company A and
other companies are deposited into accounts the companies have with the
bank. However, in other embodiments the payments made between Company A
and other companies are deposited into accounts at other financial
institutions, but the combined credit exposure application 817 can
identify if the companies involved in transactions with Company A have
other accounts at the bank through the commercial identification
information captured in block 910.

[0112] Once the companies are identified as related commercial customers
the combined credit exposure application 817 can identify related
commercial customer information such as related commercial customer
relationship information and related commercial customer account
information from the commercial exposure system 830 (or other systems and
servers that store commercial customer information and are accessed over
the network 802), as illustrated by block 914. The relationship
information captured by the combined credit exposure application 817 can
include, but is not limited to, the number of related commercial
customers who utilize products offered by the bank, related commercial
customer geographic location information (country, region, state, county,
city, zip code, street address, etc.), industry and sector information of
the related commercial customers, credit ratings, bond ratings, etc. The
related commercial customer account information can include, but is not
limited to the amount of deposits, installment loans, lines of credit,
commercial real estate loans, outstanding credit, unused lines of credit,
and total related commercial customer exposure (i.e. sum of the balances
and loans) that the related commercial customers have with the bank. In
some embodiments of the invention, the credit exposure application 817
communicates with other systems and servers at the bank, or outside of
the bank, through the network 802 in order to capture information, such
as, but not limited to, industry or sector information, information about
the company, size, number of employees, etc.

[0113] As illustrated by block 916 in FIG. 9, the combined credit exposure
application 817 then calculates the combined credit exposure report for
the customer. The combined credit exposure application 817 aggregates the
customer information, with the related consumer information and the
related commercial customer information to generate a report based on a
request by the user 803, or set up automatically, in the combined credit
exposure application 817. For example, the total amount of deposits,
credits, loans, etc. is added up for the customer, and all of the related
consumers and related commercial customers. In addition, in some
embodiments the combined credit exposure application 817 determines some
ratios of interest, such as, but not limited to, deposit-loan ratios,
consumer-commercial exposure ratios, etc.

[0114] In some embodiments of the invention the combined credit exposure
report generated is a static snapshot of the exposure at a particular
point in time. For example the information captured by the combined
credit exposure application 817, such as the customer information,
related consumer information and related commercial customer information,
may be time-stamped for a particular point in time when it was collected.
In some embodiments of the invention, the information captured by the
combined credit exposure application 817 for a particular point in time
can be compared to the same or similar information captured at another
point in time, such as the previous day, week, month, quarter, year, etc.
Thus, the combined credit exposure application 817 can determine the
exposure of a selected entity and related entities over two or more
points in time, or an interval of time, to indicate if the exposure is
improving or decaying with respect to time. Therefore, the report
generated can include the combined credit exposure at a particular point
in time, over two or more points in time, or both. For example, the
report can include the change from one date to another in the consumer
credit exposure, commercial credit exposure, total combined credit
exposure, deposit-loan ratios, consumer-commercial exposure ratios, etc.
over a period of time, to name a few metrics.

[0115] As illustrated by block 918 in FIG. 9 the information is presented
to the user 803 in a meaningful interface. In some embodiments of the
invention, the information included in the report is non-descriptive, in
that it does not identify specific related consumers or related
commercial customers, but generally provides information about groups of
consumers, groups of commercial customers, industries, sectors, etc.
However, in other embodiment the reports may contain specific descriptive
information about related consumers and related commercial customers, so
that users 803 can identify the risk and revenue exposure to specific
consumers or commercial customers. For example, in some embodiments the
reports generated are specific to individual companies, industries,
sectors, or geography. However, in other embodiments the reports can
create a snapshot of the banks exposure to a specific industry, sector,
geographic location, etc. FIGS. 6A-6C and 7A-7C illustrate embodiments of
the combined credit exposure interfaces 600, 700, which display the
reports generated by the combined credit exposure application 817 for
different types of consumer and commercial customer information. These
interfaces display one embodiment of the reports that can be generated,
it is to be understood that other types of reports can be generated by
the combined credit exposure application 817 that display other metrics
with respect to customers, related consumers, related commercial
customers, etc.

[0116] It will be appreciated that, in the banking context, embodiments of
the combined credit exposure application 817 may be used to help in both
a risk management environment, as well as in an offensive aspect of
indentifying areas that need additional exposure in both commercial
banking and consumer banking The credit exposure application 817 can be
used to create a bank risk control framework which cuts across the
consumer and commercial areas of banking to identify areas, based on
sector, industry, company, and geography that could be more risky for
additional development because of an already overexposed credit risk. The
credit exposure application 817 could be used in this sense to prevent
the bank from directing additional funds to areas that could prove to be
more risky because of too much credit exposure. The credit exposure
application 817 is used to identify and redefine the acceptable levels of
bank risk in specific sectors, industries, companies, geographies, etc.
It may also be used to optimize the bank's portfolio by identifying and
reducing tail risk. The credit exposure application 817 can be used to
reduce credit exposure to consumers employed by a customer, and
suppliers, distributors, partners, etc. related to the customer that have
credit risk, by helping to identify and utilize risk transfer vehicles
such as securitization and hedging. Furthermore, if a company suffers a
risk rating drop or covenant breach, and the bank is uncertain as to
whether to take a risk action on a customer, the bank's loan exposure to
consumers that work for the commercial customer can factor into the
decision for making additional credit available to the customer.

[0117] The combined credit exposure application 817 also provides
offensive metrics for identifying opportunities for additional revenue
streams. For example, the combined credit exposure application helps to
identify group banking opportunities at companies with good risk ratings,
but low consumer exposure. The combined credit exposure application 817
also helps identify other growth and diversification opportunities by
identifying consumers, commercial customers, industries, and sectors that
are underexposed. Other functions include helping to identify and manage
exposure allocation between sectors, industries, commercial customers,
and geographic locations. The combined credit exposure application 817
also helps to identify suppliers and distributors of companies who do not
use products from the bank, in order to create an outreach program to
initiate and deepen relationships.

[0118] The techniques for risk management and business opportunity
identification, described above, were not available or had little use
before embodiments of the present invention were developed. Embodiments
of the present invention allow a bank to create a bridge between
commercial exposure and consumer exposure to identify the data related to
the total exposure of the bank for a customer in one location for
manipulation, investigation, and analysis. Embodiments of the present
invention also allow for more effective risk management through portfolio
management, hedging, securitization, better compliance with regulators,
etc. Embodiments of the invention also improve consumer lending by
providing an increase in lending through recognized opportunities where
bank exposure as a whole is relatively less than desirable, and also
helps users exercise caution in lending to sectors, industries, or
companies where the bank has a higher concentration of exposure. The
combined credit consumer application 817 allows for increased commercial
lending by managing exposure and pricing to sectors, industries, or
companies considering overall bank exposure to each area. The combined
credit consumer application 817 also helps users recognize opportunities
to increase relationships with companies that do not use products and
services from the bank. The combined credit consumer application 817
allows users to increase investment banking opportunities through new
opportunities or mergers and acquisitions or other financial advisory
activities by recognizing under and over exposed areas, companies,
employees, suppliers, distributors, and partners.

[0119] In some embodiments of the invention the reports developed in the
combined credit consumer application 817 should be combined with other
financial information and reports to make the proper determinations for
increasing or reducing exposure in particular sectors and industries for
consumers and commercial customers.

[0120] As will be appreciated by one of ordinary skill in the art in view
of this disclosure, the present invention may be embodied as an apparatus
(including, for example, a system, machine, device, computer program
product, and/or the like), as a method (including, for example, a
business process, computer-implemented process, and/or the like), or as
any combination of the foregoing. Embodiments of the present invention
are described above with reference to flowchart illustrations and/or
block diagrams of such methods and apparatuses. It will be understood
that blocks of the flowchart illustrations and/or block diagrams, and/or
combinations of blocks in the flowchart illustrations and/or block
diagrams, can be implemented by computer-executable program instructions
(i.e., computer-executable program code). These computer-executable
program instructions may be provided to a processor of a general purpose
computer, special purpose computer, or other programmable data processing
apparatus to produce a particular machine, such that the instructions,
which execute via the processor of the computer or other programmable
data processing apparatus, create a mechanism for implementing the
functions/acts specified in the flowchart and/or block diagram block or
blocks. As used herein, a processor may be "configured to" perform a
certain function in a variety of ways, including, for example, by having
one or more general-purpose circuits perform the function by executing
one or more computer-executable program instructions embodied in a
computer-readable medium, and/or by having one or more
application-specific circuits perform the function.

[0121] These computer-executable program instructions may be stored or
embodied in a computer-readable medium to form a computer program product
that can direct a computer or other programmable data processing
apparatus to function in a particular manner, such that the instructions
stored in the computer readable memory produce an article of manufacture
including instructions which implement the function/act specified in the
flowchart and/or block diagram block(s).

[0122] Any combination of one or more computer-readable media/medium may
be utilized. In the context of this document, a computer-readable storage
medium may be any medium that can contain or store data, such as a
program for use by or in connection with an instruction execution system,
apparatus, or device. The computer-readable medium may be a transitory
computer-readable medium or a non-transitory computer-readable medium.

[0123] A transitory computer-readable medium may be, for example, but not
limited to, a propagation signal capable of carrying or otherwise
communicating data, such as computer-executable program instructions. For
example, a transitory computer-readable medium may include a propagated
data signal with computer-executable program instructions embodied
therein, for example, in base band or as part of a carrier wave. Such a
propagated signal may take any of a variety of forms, including, but not
limited to, electro-magnetic, optical, or any suitable combination
thereof. A transitory computer-readable medium may be any
computer-readable medium that can contain, store, communicate, propagate,
or transport program code for use by or in connection with an instruction
execution system, apparatus, or device. Program code embodied in a
transitory computer-readable medium may be transmitted using any
appropriate medium, including but not limited to wireless, wireline,
optical fiber cable, radio frequency (RF), etc.

[0124] A non-transitory computer-readable medium may be, for example, but
not limited to, a tangible electronic, magnetic, optical,
electromagnetic, infrared, or semiconductor storage system, apparatus,
device, or any suitable combination of the foregoing. More specific
examples (a non-exhaustive list) of the non-transitory computer-readable
medium would include, but is not limited to, the following: an electrical
device having one or more wires, a portable computer diskette, a hard
disk, a random access memory (RAM), a read-only memory (ROM), an erasable
programmable read-only memory (EPROM or Flash memory), a portable compact
disc read-only memory (CD-ROM), an optical storage device, a magnetic
storage device, or any suitable combination of the foregoing.

[0125] It will also be understood that one or more computer-executable
program instructions for carrying out operations of the present invention
may include object-oriented, scripted, and/or unscripted programming
languages, such as, for example, Java, Perl, Smalltalk, C++, SAS, SQL,
Python, Objective C, and/or the like. In some embodiments, the one or
more computer-executable program instructions for carrying out operations
of embodiments of the present invention are written in conventional
procedural programming languages, such as the "C" programming languages
and/or similar programming languages. The computer program instructions
may alternatively or additionally be written in one or more
multi-paradigm programming languages, such as, for example, F#.

[0126] The computer-executable program instructions may also be loaded
onto a computer or other programmable data processing apparatus to cause
a series of operation area steps to be performed on the computer or other
programmable apparatus to produce a computer-implemented process such
that the instructions which execute on the computer or other programmable
apparatus provide steps for implementing the functions/acts specified in
the flowchart and/or block diagram block(s). Alternatively, computer
program implemented steps or acts may be combined with operator or human
implemented steps or acts in order to carry out an embodiment of the
invention.

[0127] Embodiments of the present invention may take the form of an
entirely hardware embodiment, an entirely software embodiment (including
firmware, resident software, micro-code, etc.), or an embodiment
combining software and hardware aspects that may generally be referred to
herein as a "module," "application," or "system."

[0128] While certain exemplary embodiments have been described and shown
in the accompanying drawings, it is to be understood that such
embodiments are merely illustrative of and not restrictive on the broad
invention, and that this invention not be limited to the specific
constructions and arrangements shown and described, since various other
changes, combinations, omissions, modifications and substitutions, in
addition to those set forth in the above paragraphs, are possible. Those
skilled in the art will appreciate that various adaptations,
combinations, and modifications of the just described embodiments can be
configured without departing from the scope and spirit of the invention.
Therefore, it is to be understood that, within the scope of the appended
claims, the invention may be practiced other than as specifically
described herein.